Posts Categorized: Developers

In speech and writing, how often do we use one term — and only that term — to describe an idea? For example, if you were searching through a document for information relating to a business’ current assets, looking up only “current assets” would mean that you miss out on anything discussing cash, short-term assets,… Read more

We are all inundated with information. Even in a Google-powered world, where it’s relatively easy to find any type of content that we may seek, it can sometimes still take significant effort to pore through the search results and find the specific pieces we are interested in. For instance, say you’re interested in wearable tech.… Read more

One of our core values as a company is about giving back and supporting our community. We regularly sponsor hackathons (over 10 so far this year!) to encourage students to get started in the exciting world of machine learning. Recently, we sponsored HackPrinceton. We found Waseem Khan’s ContextCam project particularly interesting, so we reached out… Read more

Sorting content into categories is a key task for recommendation systems, as well as for general data management. We’ve talked a lot about text data lately — for example, using topic tags to improve article suggestions for your readership, and how you can build a custom text classifier for your specific industry or task. We… Read more

In our previous tutorial on customer support bots, we trained a bot using the Custom Collection API to direct customers to the team member who is best suited to assist them with their problem or query. The bot improved our team’s response times as we no longer had to rely on a human facilitator (who… Read more

I recently stumbled across an old Data Science Stack Exchange answer of mine on the topic of the “Best Python library for neural networks”, and it struck me how much the Python deep learning ecosystem has evolved over the course of the past 2.5 years. The library I recommended in July 2014, pylearn2, is no… Read more

The goal of this tutorial is to help you analyze your own Excel data using indico’s machine learning APIs — even if you have little programming experience! At the end of this tutorial you will be able to take the data from your .xlsx (Excel) files, analyze them using any of our text APIs, and… Read more

PDF, or Portable Document Format, files were developed to enable people using different operating systems to open, review, and print files without altering any of the file’s original elements or design. Successful adoption of this format over the years means that there is now a wealth of information stored in PDF files. Extracting that information… Read more

In a startup, we wear many hats. Operations does a little bit of sales, marketing does a little bit of quality assurance, engineering contributes to the blog…and everyone takes pride in helping out with customer service. For many months, we had one person managing questions we received through our little Intercom chat window (you know,… Read more

Deploying machine learning models has always been a struggle. Most of the software industry has adopted the use of container engines like Docker for deploying code to production, but since accessing hardware resources like GPUs from Docker was difficult and required hacky, driver specific workarounds, the machine learning community has shied away from this option.… Read more